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A Robust Detection Method for Moving Targets Based on Frame Difference

Author: FengYaoWen
Tutor: WuLiGang
School: Harbin Institute of Technology
Course: Control Science and Engineering
Keywords: Gaussian mixture model False alarm rate Filtering Foreground segmentation
CLC: TP391.41
Type: Master's thesis
Year: 2011
Downloads: 80
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Abstract


Moving target detection technology is a cutting-edge field of computer vision application topics and research focus. With the Internet technology and the rapid development of digital video technology, computer vision is toward intelligence and network changes. Machine Vision purpose is to study how such machines have similar human visual processing capability, enabling them to assist or even replace human work. Moving target detection field of machine vision technology is the key issue, but also a necessary dynamic visual information acquisition process. Moving target detection is almost the beginning of all the visual monitoring system aimed at the picture with the moving target areas associated with other regions separated. Moving target detection research has a strong theoretical and practical significance. Moving target detection technology has broad application space and great potential value. In recent years, many scholars at home and abroad has been committed to moving target detection studies, some well-known detection systems have emerged. Existing methods are mostly targeted at a specific background, the background of a certain prominent factors achieved good results, and can not completely solve the complex background to the impact of moving target detection. Moving target detection is not only a hot topic of theoretical, but also an engineering problem to be solved. The actual visual system working environment is very complex, very urgent to improve the applicability of the system. The applicability of the system to improve vision must be addressed in a complex scene robust moving target detection problem, the solution lies in: a) the background of complex statistical modeling; 2) uses robust detection techniques. In view of this, the paper moving target detection in complex background done in-depth research, and presents a moving target detection algorithm: a study of the principles of inter-frame difference method to analyze the traditional inter-frame difference method advantages and disadvantages to each pixel of the frame difference sequence as a modeling object, using Gaussian mixture model for the data modeling. (2) the introduction of the statistics and false alarm rate detection theory and concepts. Based on threshold detection method for detection threshold and false alarm rate as a function of, proposed a simple linear regression based background update strategy. After the above method to find the threshold of the differential image binarization processing, the moving object outline clearly visible, complex background converted to discrete points around the contour-like noise. 3 compares the various filtering method and edge detection method is proposed to focus on non-zero pixels denoising method based segmentation method and prospects. These methods have been a large number of experimental verification, and achieved satisfactory results.

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CLC: > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer applications > Information processing (information processing) > Pattern Recognition and devices > Image recognition device
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